Research interests

My research area is mainly focused on Machine Learning.
I am specially interested in generative models
Specifically, I have applied copula theory to different subjects such as

  • Wind Resource Estimation
  • E-Commerce Fraud Detection
  • Longitudinal Data Modeling
  • Estimation of Distribution Algorithms
In addition, I am recently involved in visual tracking, which has led me to novel techniques such as Deep Learning.

Works in the news

Consulting

  • AMS Geomatics (2018) Co-Principal investigator
  • BE CAE & Test (2021) Principal investigator
  • BielGlasses (2017, 18, 19, 20, 21) Research staff
  • Ecoembes (2017) Research staff
  • EverVest (2014) Principal investigator
  • Navmii (2017) Research staff
  • PatternEx (2016) Principal investigator
  • PixelLabs (2017, 21) Research staff
  • Simbiotica (2018) Principal investigator

Competitive Projects

  • EyeOT Smart eyes on digital twins

    2022 -- 2024 Agencia Estatal de Investigación (PID2021-128362OB-I00) Co-principal Investigator

  • POLLUTWIN High Fidelity Digital Twin of Pollutant Mobile Sources in Cities

    2022 -- 2024 Agencia Estatal de Investigación (TED2021-129162B-C22) Research staff

  • FotoCaos New computational methods for simulating and optimization of photochemical processes

    2019 -- 2021 Comunidad de Madrid (Y2018/EMT-5062) Research staff

  • SmartEyes Smart Eyes for Smart Cities

    2019 -- 2021 MINECO (RTI2018-098743-B-I00) Co-Principal investigator

  • HARAMI Human Activity Recognition with AMbient Intelligence methods

    2016 -- 2018 MINECO (TIN2015-69542-C2-1-R) Research staff

  • IYELMO PaaS for trading

    2011 -- 2014 INNPACTO – IPT-2011-1198-430000 Research staff

  • TEDICO controllers design techniques developed with the space of parameters, multirate and fractional order calculus methods

    2004 -- 2007 CICYT - DPI2004-05903 Ph.D. student

Postdoc projects and Visiting faculty

  • Massachusetts Institute of Technology Invited by Dr. Kalyan Veeramachaneni (LIDS)

    January, 2018

  • Massachusetts Institute of Technology Invited by Dr. Una-May O'Reilly (CSAIL)

    September -- December, 2010 September -- December, 2013

  • University of New Mexico Time Series Analysis and Prediction using Copulas and Wavelets. Applications in Control Engineering

    January -- August, 2009 José Castillejo research fellowship (JC2008-00421)

  • RCC at Harvard Design of Control Systems regarding Stochastic Dependencies

    Sept--Dec. 2008, 2009, 2010 RCC at Harvard research fellowship

Selected publications

  • S Hernandez-Garcia, A Cuesta-Infante, J.A. Moreno-SanSegundo and A.S. Montemayor: "Deep reinforcement learning for automated search of model parameters: Photo-Fenton wastewater disinfection case study”. Neural Computing and Applications, 35(2): 1379-1394 (2023)
  • L. Llopis-Ibor, C. Beltran-Royo, J.J. Pantrigo, A. Cuesta-Infante: "Fast Incremental Learning by Transfer Learning and Hierarchical Sequencing”. Expert Systems with Applications, 212, 118580 (2023)
  • L. Xu, A. Cuesta-Infante, L. Berti-Équille, K. Veeramachaneni: "R & R: Metric-guided Adversarial Sentence Generation". Findings of AACL/IJCNLP, 438-452 (2022).
  • L. Xu, L. Berti-Equille, A. Cuesta-Infante, K. Veeramachaneni: "In situ Augmentation for Defending Against Adversarial Attacks on Text Classifiers". KDD Workshop on Adversarial Machine Learning (2022). Best paper award.
  • Y. Sun, I. Ramírez, A. Cuesta-Infante, K. Veeramachaneni: "Towards Reducing Biases in Combining Multiple Experts Online". IJCAI, 3024-3030 (2021)
  • A. Geiger, D. Liu, S. Alnegheimish, A. Cuesta-Infante, K. Veeramachaneni: "TadGAN: Time Series Anomaly Detection Using Generative Adversarial Networks". IEEE Int. Conf. on Big Data, 33-43 (2020)
  • I. Ramírez, A. Cuesta-Infante, E. Schiavi, J.J. Pantrigo: "Bayesian Capsule Networks for 3D human pose estimation from single 2D images". Neurocomputing, 379: 67-73 (2020)
  • I. Ramírez, A. Cuesta-Infante, J.J. Pantrigo, A.S. Montemayor, et al.: "Convolutional neural networks for computer vision-based detection and recognition of dumpsters". Neural Computing and Applications 32(17): 13203-13211 (2020)
  • L. Xu, M. Skoularidou, A. Cuesta-Infante, K. Veeramachaneni: "Modeling Tabular data using Conditional GAN". NeurIPS, 7333-7343 (2019)
  • Y. Sun, A. Cuesta-Infante, K. Veeramachaneni: "Learning Vine Copula Models For Synthetic Data Generation". AAAI, 5049-5057 (2019)
  • T. Swearingen, W. Drevo, B. Cyphers, A.Ross, A. Cuesta-Infante, K. Veeramachaneni: "ATM: A distributed, collaborative, scalable system for automated machine learning". IEEE Int. Conf. on Big Data, 151-162 (2017)
  • I. Arnaldo, A. Cuesta-Infante, A. Arun, M. Lam, C. Bassias, K. Veeramachaneni: "Learning Representations for Log Data in Cybersecurity". Int. Symp. on Cyber Security Cryptography and Machine Learning, 250-268, (2017)
  • B. Lacabex, A. Cuesta-Infante, A.S. Montemayor, J.J. Pantrigo: "Lightweight tracking-by-detection system for multiple pedestrian targets". Integrated Computer-Aided Engineering 23(3): 299-311 (2016)
  • K. Veeramachaneni, A. Cuesta-Infante, U.M. O'Reilly: "Copula Graphical Models for Wind Resource Estimation". IJCAI 2015: 2646-2654
  • J.I. Hidalgo, J.M. Colmenar, J.L. Risco-Martín, A. Cuesta-Infante, E. Maqueda, M. Botella, J.A. Rubio: "Modeling glycemia in humans by means of Grammatical Evolution". Applied Soft Computing 20: 40-53 (2014)
  • More at ORCID ( 0000-0002-3328-501X ) , Scopus ( 35955730700 ) , Publons/WoS ( L-3708-2014 ) , Google Scholar ( OQsC-14AAAAJ ) and DBLP ( Q58993442 )

Teaching

since 2016 Universidad Rey Juan Carlos


Computer Security, Information Systems, Developing Video Games with Artificial Intelligence, Video Games Engineering

1999-2015 C.E.S. Felipe II
(Universidad Complutense de Madrid)


Logic Design, Lab. of Computer Engineering, Networks, Computer Security, Data Warehouses and Data Mining

2009 "Problemas de Estructura y Arquitectura de Computadores" (Book in spanish about Computer Architecture assignments)


A. Cuesta, J.I. Hidalgo, J. Lanchares, J.L. Risco.
ISBN: 97-884832259-1-2, Ed. Pearson.

Education

  • Ph.D. in Computer Science UNED

    2016

  • Ms.S. in Physics UCM

    1998

  • Faculty position Associate Professor

    2021